How Effective Are Customer Interaction Analytics?

The editors of the Genesys Blog are pleased to present a guest post from Steve Morell, global contact center industry expert and founder of ContactBabel.

Over the past 12 months, ContactBabel has carried out over 400 interviews with US and UK contact center operations. Respondents were asked how effective customer interaction analytics solutions (which include speech analytics as well as text analytics) are for assisting with critical operational and strategic objectives. The amalgamated findings are presented in the following chart.

In over half of cases, customer interaction analytics were viewed as being ‘very effective’ in helping with Quality Management (QM).  Being able to monitor 100% of conversations with 100% of agents means that the chances of listening to the right calls – whether for agent evaluation or business insight – are far higher than in a random QM environment.  Linking this information with metadata such as call outcomes, sales success rates, and other business metrics means that the most successful behaviors and characteristics can be identified and shared across agent groups.

The second most valuable use of customer interaction analytics was reported to be targeting agent training needs, as it can flag and analyze cases of talk-over as well as silence detection, which can respectively indicate suboptimal conversational skills or a lack of agent knowledge. Additionally, being able to analyze 100% of interactions, including outcomes, makes it far easier for an organization to be able to uncover specific topics about which each agent may need additional training or coaching and disseminate best practices more widely.

One of the most widely uses of customer interaction analytics, especially in the US marketplace, is ensuring compliance with regulations on 100% of interactions. Many businesses, especially those in finance, insurance, public sector and debt collection, have become encumbered with regulations which they must follow strictly, with potentially expensive penalties for failure, including heavy fines and criminal prosecution. A spin-off benefit from this, often seen in the debt collection industry, is that the chance to understand the type of agent language and behavior that yields the best results can then be shared with underperforming agents as well as feeding into an improved scripting process.

No other contact center solution apart from customer interaction analytics can provide a solid understanding of why customers are contacting your company. And this is one of the most interesting opportunities, especially as the sophistication of solutions, and businesses’ experience of how best to use analytics, continues to improve. The automatic categorization of conversations, based on the types of words and phrases that typically get used within these types of interactions, is a starting point. Analytics solutions can then add other types of data, such as desktop activity or account status, and the tracking of phrase usage compared with its historical use can quickly indicate and identify issues that can be handed to the relevant department, as well as being fed into longer term strategic initiatives.

While other uses of customer interaction analytics such as customer sentiment analysis or gathering competitive information are not yet seen in as positive a light as the more operational uses, the potential commercial insights to be gained are massive. While existing analytics solutions have perhaps been more focused upon the quick wins associated with reducing quality management cost and effort, as well as ensuring compliance, the company-wide benefits associated with extracting and understanding the insight from every customer interaction are invaluable.

To gain more insights on how a customer interaction analytics solution can be a competitive advantage, download the ContactBabel report Inner Circle Guide to Customer Interaction Analytics.